Synaptic activity induces input‐specific rearrangements in a targeted synaptic protein interaction network

Abstract

Cells utilize dynamic, network-level rearrangements in highly interconnected protein interaction networks to transmit and integrate information from distinct signaling inputs. Despite the importance of protein interaction network dynamics, the organizational logic underlying information flow through these networks is not well understood. Previously, we developed the quantitative multiplex co-immunoprecipitation platform, which allows for the simultaneous and quantitative measurement of the amount of co-association between large numbers of proteins in shared complexes. Here, we adapt quantitative multiplex co-immunoprecipitation to define the activity-dependent dynamics of an 18-member protein interaction network in order to better understand the underlying principles governing glutamatergic signal transduction. We first establish that immunoprecipitation detected by flow cytometry can detect activity-dependent changes in two known protein-protein interactions (Homer1-mGluR5 and PSD-95-SynGAP). We next demonstrate that neuronal stimulation elicits a coordinated change in our targeted protein interaction network, characterized by the initial dissociation of Homer1 and SynGAP-containing complexes followed by increased associations among glutamate receptors and PSD-95. Finally, we show that stimulation of distinct glutamate receptor types results in different modular sets of protein interaction network rearrangements, and that cells activate both modules in order to integrate complex inputs. This analysis demonstrates that cells respond to distinct types of glutamatergic input by modulating different combinations of protein co-associations among a targeted network of proteins. Our data support a model of synaptic plasticity in which synaptic stimulation elicits dissociation of pre-existing multiprotein complexes, opening binding slots in scaffold proteins and allowing for the recruitment of additional glutamatergic receptors. Open Science: This manuscript was awarded with the Open Materials Badge. For more information see: https://cos.io/our-services/open-science-badges/.

Homeostatic Plasticity Requires Remodeling of the Homer-Shank Interactome

“…The quantitative multiplex immunoprecipitation (QMI) panel described in this report contains 21 validated synapse-associated proteins-receptors, scaffolds, and downstream signaling molecules (Table 1) and measures 380 binary PiSCES for each experiment (Lautz et al, 2018(Lautz et al, , 2019. QMI takes advantage of fluorophore-embedded microspheres ("beads") to immunoprecipitate multiple protein targets from a single sample simultaneously (Lautz et al, 2018;Smith et al, 2016). Biotinyated probe antibodies detect co-associated proteins, and, following streptavidin-PE secondary labeling, the median fluorescence intensity (MFI) of each IP-probe combination is measured on a flow cytometer and averaged across technical replicates (see methods) ( Fig.…”

“…Primary cultures of cortical neurons were prepared as previously described (Lautz et al, 2018). Briefly, whole cortex from P0-P1mouse neonates was dissociated using papain (Worthington) and plated at a density of 1.0x10 6 cells/mL onto 6-well plates treated with poly-D-lysine.…”

“…QMI was performed as described previously (Lautz et al, 2018;Smith et al, 2016). Briefly, a master mix containing equal numbers of each antibody-coupled Luminex bead was prepared and distributed to lysates containing equal amounts of protein and incubated overnight on a rotator at 4°C.…”

“…The resulting bead-probe complexes were washed 3 times with Fly-P buffer, incubated for 30 minutes with streptavidin-PE on ice, washed another 3 times, resuspended in 125µl ice cold Fly-P buffer, and processed for fluorescence using a customized refrigerated Bio-Plex 200 (Smith et al, 2016). Antibody clone names, catalog numbers, and lot numbers are the same as in (Lautz et al, 2018).…”

“…CNA: Modules of PiSCES that co-varied with experimental conditions were identified using CNA as described in (Lautz et al, 2018;Smith et al, 2016). Briefly, bead distributions used in ANC were collapsed into a single MFI for every PiSCES and averaged across technical replicates for input into the WGCNA package for R (Langfelder and Horvath, 2008).…”